Attention mechanism.
Attention can be viewed as the process of adjusting or allocating activation intensity towards the most informative or useful locations of inputs.
There are several methods for exploiting attention mechanism to improve image classification [1]}, [2]} and object detection [3]} tasks. GFR-DSOD [3]} proposed a gated CNN for object detection based on [5]} that passes messages between features from different resolutions and used gated functions to control information flow. SENet [2]} used attention mechanism to model channel-wise relationships and enhanced the representation ability of modules through
the networks. In this paper, we introduce a simple attention-based region selection that can find out the most discriminative parts spatially.
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